import time


class _demo_mag(object):
    def showData_demo(self):
        all_data = []

        data_1 = {}
        data_1['location'] = 'l'
        data_1['url'] = '1'
        data_1['title'] = '就业岗位最多的前10个城市'
        data_1['abstract'] = '目前国内本专业就业岗位最多的五座城市是北京,上海,广州,深圳,成都.这也与人们预期的结果相符.'
        data_1['author'] = '官方发布'
        data_1['time'] = '2017/8/15'
        now_time_m = int(time.strftime('%m',time.localtime(time.time()))) - 8
        now_time_d = int(time.strftime('%d',time.localtime(time.time())))
        data_1['time_D'] = str(now_time_m) + '月' + str(now_time_d) + '天前'
        all_data.append(data_1)


        data_2 = {}
        data_2['location'] = 'r'
        data_2['url'] = '2'
        data_2['title'] = '部门城市工资情况'
        data_2['abstract'] = '目前国内本专业就业岗位最多的五座城市是北京,上海,广州,深圳,成都.这也与人们预期的结果相符.'
        data_2['author'] = '官方发布'
        data_2['time'] = '2017/9/1'
        now_time_m = int(time.strftime('%m', time.localtime(time.time()))) - 8
        now_time_d = int(time.strftime('%d', time.localtime(time.time())))
        data_2['time_D'] = str(now_time_m) + '月' + str(now_time_d) + '天前'
        all_data.append(data_2)


        data_3 = {}
        data_3['location'] = 'l'
        data_3['url'] = '3'
        data_3['title'] = '全国部分城市就业量分布'
        data_3['abstract'] = '目前国内本专业就业岗位最多的五座城市是北京,上海,广州,深圳,成都.这也与人们预期的结果相符.'
        data_3['author'] = '官方发布'
        data_3['time'] = '2017/10/7'
        now_time_m = int(time.strftime('%m', time.localtime(time.time()))) - 8
        now_time_d = int(time.strftime('%d', time.localtime(time.time())))
        data_3['time_D'] = str(now_time_m) + '月' + str(now_time_d) + '天前'
        all_data.append(data_3)

        data_4 = {}
        data_4['location'] = 'r'
        data_4['url'] = '4'
        data_4['title'] = '就业岗位数量南丁格尔图'
        data_4['abstract'] = '目前国内本专业就业岗位最多的五座城市是北京,上海,广州,深圳,成都.这也与人们预期的结果相符.'
        data_4['author'] = '官方发布'
        data_4['time'] = '2017/10/7'
        now_time_m = int(time.strftime('%m', time.localtime(time.time()))) - 9
        now_time_d = int(time.strftime('%d', time.localtime(time.time())))
        data_4['time_D'] = str(now_time_m) + '月' + str(now_time_d) + '天前'
        all_data.append(data_4)

        data_5 = {}
        data_5['location'] = 'l'
        data_5['url'] = '5'
        data_5['title'] = '全国部分城市就业量分布'
        data_5['abstract'] = '目前国内本专业就业岗位最多的五座城市是北京,上海,广州,深圳,成都.这也与人们预期的结果相符.'
        data_5['author'] = '官方发布'
        data_5['time'] = '2017/10/7'
        now_time_m = int(time.strftime('%m', time.localtime(time.time()))) - 9
        now_time_d = int(time.strftime('%d', time.localtime(time.time())))
        data_5['time_D'] = str(now_time_m) + '月' + str(now_time_d) + '天前'
        all_data.append(data_5)

        data_6 = {}
        data_6['location'] = 'r'
        data_6['url'] = '6'
        data_6['title'] = '就业岗位数量南丁格尔图'
        data_6['abstract'] = '目前国内本专业就业岗位最多的五座城市是北京,上海,广州,深圳,成都.这也与人们预期的结果相符.'
        data_6['author'] = '官方发布'
        data_6['time'] = '2017/10/7'
        now_time_m = int(time.strftime('%m', time.localtime(time.time()))) - 10
        now_time_d = int(time.strftime('%d', time.localtime(time.time())))
        data_6['time_D'] = str(now_time_m) + '月' + str(now_time_d) + '天前'
        all_data.append(data_6)

        data_7 = {}
        data_7['location'] = 'l'
        data_7['url'] = '7'
        data_7['title'] = '全国部分城市就业量分布'
        data_7['abstract'] = '目前国内本专业就业岗位最多的五座城市是北京,上海,广州,深圳,成都.这也与人们预期的结果相符.'
        data_7['author'] = '官方发布'
        data_7['time'] = '2017/10/7'
        now_time_m = int(time.strftime('%m', time.localtime(time.time()))) - 10
        now_time_d = int(time.strftime('%d', time.localtime(time.time())))
        data_7['time_D'] = str(now_time_m) + '月' + str(now_time_d) + '天前'
        all_data.append(data_7)

        data_8 = {}
        data_8['location'] = 'r'
        data_8['url'] = '8'
        data_8['title'] = '就业岗位数量南丁格尔图'
        data_8['abstract'] = '目前国内本专业就业岗位最多的五座城市是北京,上海,广州,深圳,成都.这也与人们预期的结果相符.'
        data_8['author'] = '官方发布'
        data_8['time'] = '2017/10/7'
        now_time_m = int(time.strftime('%m', time.localtime(time.time()))) - 10
        now_time_d = int(time.strftime('%d', time.localtime(time.time())))
        data_8['time_D'] = str(now_time_m) + '月' + str(now_time_d) + '天前'
        all_data.append(data_8)


        return all_data
